VAR has gained widespread popularity due to its next-scale prediction paradigm. However, it faces substantial performance bottlenecks when handling complex scenes with multiple objects and attributes. Existing diffusion-based enhancement methods fail to adequately address the unique challenge of cross-scale error propa...
Zhen-Nan Chen, Tianxing Shi, Pengcheng Xu et al.· 0 citations
Face Super-Resolution (FSR) faces a critical challenge in balancing reconstruction quality with computational efficiency when deployed on resource-constrained devices. While existing methods leverage CNNs or transformers, they are constrained by limited receptive fields or high computational complexity. To achieve both...
Yun-Zhe Xu, Chen Zhao, Zhi-Zhou Chen et al.· IEEE Transactions on Image P...· 0 citations
InstructVVT is proposed, an instruction-driven and reference-guided video virtual try-on framework based on a Diffusion Transformer that operates without inference-time spatial priors that outperforms state-of-the-art open-source methods in garment fidelity, structural preservation, and temporal consistency, despite re...
Di Shao, Song-Han Wu, Xin-Yu Chen et al.· 0 citations
We use cookies to run the site and, with your consent, for analytics and to show ads.
See our Cookie Policy.